Integrating Geospatial and Real Time Technologies for Risk zone monitoring in Periyar Tiger Reserve, India.

Abstract

There are numerous monitoring technologies available today, owing to the rapid advancements in technology and the increasing demand for safety and security in forests. Real-time monitoring with AI cameras, which are commonly utilized for creating and updating real-time features through surveillance, stands out as one of the most effective monitoring solutions. The objective of this current research is to monitor various risk zones within the Periyar Tiger Reserve by integrating real-time AI camera with geographic data. AI cameras were strategically placed using spatial analysis techniques. Leveraging Geographic Information System (GIS) technology, the system facilitates the spatiotemporal management of multiple cameras and their associated data. The spatial distribution and monitoring range of the AI cameras are depicted on the GIS map, along with the layout densities of the cameras and other pertinent information stored in a geospatial database. Additionally, merging various risk areas identified from past incidents with the camera locations enhances the system's capability to establish accurate topological connections between cameras and other points of interest. The results revealed that only 13% of the risk zone was observable from the nine available Real Time Monitoring towers. However, with the addition of 51 more towers, the visibility of the risk zone would increase to 40%. The remaining 15% of the risk zones were not visible through the existing infrastructure. To address this visibility gap, if permitted by the Wildlife Protection Act, wired communication may need to be implemented instead of wireless for monitoring these areas.